I. Field of the Invention
This invention relates generally to medical electronic diagnostic and/or treatment apparatus and more particularly to an implantable device having means for logging heart rate variability data over extended time periods for subsequent read-out and analysis.
II. Discussion of the Prior Art
Currently available implantable cardiac pacemakers and defibrillators are capable of collecting and storing a variety of information relating to the instantaneous electrical response of the heart and providing this information in real time, via telemetry link, to an external programmer which may readily be equipped with substantial data processing, storage and display resources. Certain other implantable devices are capable of logging a limited amount of parametric data, typically in the form of various event counters, which is retained in the device for future telemetry and analysis. These arrangements provide useful, but limited, information regarding the status of the heart or progression of the disease.
Accurate diagnosis requires evaluation of extensive data over an extended period of time. Long-term telemetry of raw data from an implanted device is undesirable because the low energy available to the implanted transmitter requires that the external receiver be worn by the patient in close proximity to the implanted device. Even then, the transmission of voluminous raw data may prematurely deplete the implanted battery. The preferred device currently used for logging diagnostically useful cardiac data is known as a Holter monitor. It is an external data recorder which monitors and stores cardiac electrical data sensed via surface EKG electrodes. It is desirable to incorporate the data logging function exemplified by the Holter monitor into the implantable pacemaker. However, generally speaking, prior art implantable cardiac devices, such as pacemakers, lack the memory capacity to store the voluminous raw data and/or the power to telemeter it. Well known signal compression techniques offer insufficient compression.
Lossless signal compression techniques, such as run length encoding, are well known. Since only redundant elements of the signal are eliminated all of the raw data is recoverable from the compressed signal with exactly the same resolution that it was quantized. However, all lossless compression techniques suffer from an insufficient compression ratio and an intolerable processing load. The highest compression ratios are achieved by first extracting a feature, or set of features, from the raw data, which is well correlated to the cardiac diagnostic process, and then employing lossy compression on the extracted features. Ideally, lossy data compression allows most of the data to be discarded, preserving only the minimum set of data required to adequately characterize the extracted features.
Heart Rate Variability (HRV) has been identified as a feature of cardiac activity which is particularly useful for both diagnosis and prognosis. HRV is defined as a measure of the beat-to-beat variance in sinus cycle length over a period of time. It is used as a measure of parasympathetic tone. It has been determined that individuals with diminished HRV have reduced vagal tone and probably are at increased risk of death following myocardial infarction. Various researchers have employed spectral analysis to characterize HRV. (See Coumel et al., "Heart Rate and Heart Rate Variability in Normal Young Adults", J. Cardiovascular Electrophysiology, Vol. 5, No. 11, November 1994.) Others have elected to characterize Heart Rate Variability by considering the beat-to-beat variability in heart rate. (See Ori, et al., "Heart Rate Variability", Clinics, Vol. 10, No. 3, August 1992.) This beat-to-beat characterization has been expanded to a two-dimensional histogram which displays the probability density function of the absolute beat-to-beat interval difference as a function of interval. The process of forming such a two-dimensional histogram is defined as "binning". This process will be subsequently described in detail. In summary, although the prior art shows several ways that heart rate variability data, accumulated over an extended period of time, may be processed to make the data more understandable to a clinician, we are not aware of any teaching of how logging of HRV data might be accomplished within an implantable pacemaker.